Genetics

CCPred: Global and population-specific colorectal cancer prediction and metagenomic biomarker identification at different molecular levels using machine learning techniques.

Colorectal cancer (CRC) ranks as the third most common cancer globally and the second leading cause of cancer-related deaths. Recent research highlights the pivotal role of the gut microbiota in CRC development and progression. Understanding the complex interplay between disease development and metagenomic data is essential for CRC diagnosis and treatment. Current computational models employ machi...

Interpreting cis-regulatory interactions from large-scale deep neural networks.

The rise of large-scale, sequence-based deep neural networks (DNNs) for predicting gene expression has introduced challenges in their evaluation and interpretation. Current evaluations align DNN predictions with orthogonal experimental data, providing insights into generalization but offering limited insights into their decision-making process. Existing model explainability tools focus mainly on m...

Predicting structure-targeted food bioactive compounds for middle-aged and elderly Asians with myocardial infarction: insights from genetic variations and bioinformatics-integrated deep learning analysis.

Myocardial infarction (MI) is a significant global health issue. Despite the advances in genome-wide association studies, a complete genetic and molec...

Salivary detection of Chikungunya virus infection using a portable and sustainable biophotonic platform coupled with artificial intelligence algorithms.

The current detection method for Chikungunya Virus (CHIKV) involves an invasive and costly molecular biology procedure as the gold standard diagnostic...

The application value of support vector machine model based on multimodal MRI in predicting IDH-1mutation and Ki-67 expression in glioma.

PURPOSE: To investigate the application value of support vector machine (SVM) model based on diffusion-weighted imaging (DWI), dynamic contrast-enhanc...

Splam: a deep-learning-based splice site predictor that improves spliced alignments.

The process of splicing messenger RNA to remove introns plays a central role in creating genes and gene variants. We describe Splam, a novel method fo...

Identification of Disulfidptosis-Related Genes in Ischemic Stroke by Combining Single-Cell Sequencing, Machine Learning Algorithms, and In Vitro Experiments.

BACKGROUND: Ischemic stroke (IS) is a severe neurological disorder with a pathogenesis that remains incompletely understood. Recently, a novel form of...

Deep Learning-Based Blood Abnormalities Detection as a Tool for VEXAS Syndrome Screening.

INTRODUCTION: VEXAS is a syndrome described in 2020, caused by mutations of the UBA1 gene, and displaying a large pleomorphic array of clinical and he...

RNAfcg: RNA Flexibility Prediction Based on Topological Centrality and Global Features.

The dynamics of RNAs are related intimately to their functions. Molecular flexibility, as a starting point for understanding their dynamics, has been ...

Machine learning reveals the transcriptional regulatory network and circadian dynamics of PCC 7942.

is an important cyanobacterium that serves as a versatile and robust model for studying circadian biology and photosynthetic metabolism. Its transcri...

Construction of a molecular diagnostic system for neurogenic rosacea by combining transcriptome sequencing and machine learning.

Patients with neurogenic rosacea (NR) frequently demonstrate pronounced neurological manifestations, often unresponsive to conventional therapeutic ap...

Deep Learning-Based Barley Disease Quantification for Sustainable Crop Production.

Net blotch disease caused by is a major fungal disease that affects barley () plants and can result in significant crop losses. In this study, we dev...

Bioinformatics challenges for profiling the microbiome in cancer: pitfalls and opportunities.

Increasing evidence suggests that the human microbiome plays an important role in cancer risk and treatment. Untargeted 'omics' techniques have accele...

Machine-Learning Analysis of Streptomyces coelicolor Transcriptomes Reveals a Transcription Regulatory Network Encompassing Biosynthetic Gene Clusters.

Streptomyces produces diverse secondary metabolites of biopharmaceutical importance, yet the rate of biosynthesis of these metabolites is often hamper...

A Machine Learning Method for RNA-Small Molecule Binding Preference Prediction.

The interaction between RNA and small molecules is crucial in various biological functions. Identifying molecules targeting RNA is essential for the i...

Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies.

Large-scale, multi-ethnic whole-genome sequencing (WGS) studies, such as the National Human Genome Research Institute Genome Sequencing Program's Cent...

Developing a Machine Learning 'Smart' Polymerase Chain Reaction Thermocycler Part 2: Putting the Theoretical Framework into Practice.

The introduction of PCR into forensic science and the rapid increases in the sensitivity, specificity and discrimination power of DNA profiling that f...

Comparison and benchmark of deep learning methods for non-coding RNA classification.

The involvement of non-coding RNAs in biological processes and diseases has made the exploration of their functions crucial. Most non-coding RNAs have...

CONSTRUCTING A DIAGNOSTIC PREDICTION MODEL TO ESTIMATE THE SEVERE RESPIRATORY SYNCYTIAL VIRUS PNEUMONIA IN CHILDREN BASED ON MACHINE LEARNING.

Background : Severe respiratory syncytial virus (RSV) pneumonia is a leading cause of hospitalization and morbidity in infants and young children. Ear...

DeepDBS: Identification of DNA-binding sites in protein sequences by using deep representations and random forest.

Interactions of biological molecules in organisms are considered to be primary factors for the lifecycle of that organism. Various important biologica...